Adaptive Mesh Refinement and Load Balancing Techniques for Particulate Flow Simulations

Beitrag bei einer Tagung
(Abstract zum Poster)


Details zur Publikation

Autorinnen und Autoren: Rettinger C
Jahr der Veröffentlichung: 2018


Abstract










Particulate
flow simulations of geometrically fully resolved particles enable
accurate predictions from first principles but their high
computational cost usually limits the admissible system sizes
significantly.


Here,
we present two distinct approaches to reduce these costs: adaptive
mesh refinement (AMR) and dynamic load balancing.


In AMR,
the computational grid features a fine resolution only in certain,
temporally and spatially changing regions of interest, e.g. around
the particles, whereas it is coarsened elsewhere.


Load
balancing, on the other hand, aims to distribute the computational
load evenly among the available resources to improve their
utilization which effectively reduces the time to solution.


FAU-Autorinnen und Autoren / FAU-Herausgeberinnen und Herausgeber

Rettinger, Christoph
Lehrstuhl für Informatik 10 (Systemsimulation)


Zitierweisen

APA:
Rettinger, C. (2018). Adaptive Mesh Refinement and Load Balancing Techniques for Particulate Flow Simulations. Poster presentation at CoSaS - International Symposium on Computational Science at Scale, Erlangen, DE.

MLA:
Rettinger, Christoph. "Adaptive Mesh Refinement and Load Balancing Techniques for Particulate Flow Simulations." Presented at CoSaS - International Symposium on Computational Science at Scale, Erlangen 2018.

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Zuletzt aktualisiert 2019-24-04 um 06:21